I plan to do a numerical integrals as default and keep MC sampling to be there because it is mentioned in the book. GPs usually do not scale but there are some interesting works that use exotic kernels or approximations that make them useable with large data. Simple GPs work very well with few number of samples and high dimensions (curse of dimensionality), that is at least what I found them to be most useful.